Recovering writing traces in off-line handwriting recognition: using a global optimization technique

Off-line handwriting recognition is constrained by the lack of time information. This paper describes an approach to derive sequence information from a written word. The underlying representation of the word used is a graph with nodes and edges resulting from a skeletonization process. The writing p...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 3; pp. 150 - 154 vol.3
Main Author Jager, S.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 1996
Subjects
Automation
Handwriting recognition
Hardware
Hidden Markov models
Image recognition
Image reconstruction
Personal digital assistants
Skeleton
Traveling salesman problems
Writing
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ISBN9780818672828
081867282X
ISSN1051-4651
DOI10.1109/ICPR.1996.546812

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Summary:Off-line handwriting recognition is constrained by the lack of time information. This paper describes an approach to derive sequence information from a written word. The underlying representation of the word used is a graph with nodes and edges resulting from a skeletonization process. The writing path is reconstructed by assuming that the writer has used a path with least curvature, i.e. reconstruction is realized as a global optimization process, which consists of solving a travelling salesman problem.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.546812